Observation of physical entities and phenomena is also an important part of research in the natural sciences. This method is often used by psychological, social and market researchers to understand how people act in real-life situations. Observations allow you to gather data on behaviours and phenomena without having to rely on the honesty and accuracy of respondents. Evaluating satisfaction with a company’s products or an organization’s services.Gauging public opinion on political and social topics.Describing the demographics of a country or region.Survey research allows you to gather large volumes of data that can be analyzed for frequencies, averages and patterns. The research design should be carefully developed to ensure that the results are valid and reliable. non-probability samplingĭiscover proofreading & editing Descriptive research methodsĭescriptive research is usually defined as a type of quantitative research, though qualitative research can also be used for descriptive purposes. This cannot be repaired after the course is finished. The lecturers can impose additional restrictions on the participations in the tests: only students showing sufficient participation in the course will be allowed to take part in the tests. Results for a partial test/assignment are only valid until the following semester. The minimum mark for the partial exams must be at least 5.0 and the final mark must be at least 5.5 (so a 5.0 for one of the partial exams can be compensated via a 6.0 or higher for the other partial exam).įor both partial tests and the assignment there is a retake offered. The assignment is graded ‘pass’ or ‘fail’, and must be passed to complete the course.īoth exams count for 50% of the final mark. Although participation in lectures, tutorials and discussion boards is not formally required, it is strongly recommended.įor this course there are two partial exams and an assignment. Although lectures and tutorials will not be organized for PhD students separately, the teachers will create a separate ‘niche’ where you can meet fellow PhD students. We expect that PhD students who register for this course participate actively. You follow this course together with pre-master students of the faculty BMS. Finally, they will get a basic understanding of descriptive and inferential data analysis. During the course, students will develop a first understanding of the concepts of validity and reliability, and will comprehend factors that may undermine (measurement/internal/external) validity of research. They will also learn to select from various correlational and experimental research designs and different data collection methods to answer these research questions. Students will learn to formulate clear and answerable empirical research questions. testing theories) and research in the context of problem solving and design will be discussed. The role of research in the context of the empirical cycle (i.e. This course introduces the basic principles of empirical research in the social sciences. draw conclusions and report about the results of a basic data analysis.describe the relationship between variables, using bivariate tables and scatterplots.describe data, using an appropriate statistical program, in frequency tables, bar charts, histograms and box plots.sample data from a larger population, are aware of possible biases introduced in the selection process and are aware of the idea of statistical inference based on sampled data.develop measurement instruments and to assess their reliability and validity.select an appropriate research design, and have knowledge about the factors that may undermine validity associated with the various designs.identify and comprehend the implications of a causal statement (correlation, time order and the absence of a third variable).formulate of a well-phrased and testable causal hypothesis.formulate a clear empirical research questions, with clear units of analysis, variables and with a well-defined descriptive and/or explanatory aim.This blended learning course is aimed at PhD candidates who have little or no experience with empirical research and data analysisĪfter completion of this course students will be able to:
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